Predicting the suitability of photocatalysts for water splitting using Koopmans spectral functionals: The case of TiO 2 polymorphs
Abstract
Photocatalytic water splitting has attracted considerable attention for renewable energy production. Since the first reported photocatalytic water splitting by titanium dioxide, this material remains one of the most promising photocatalysts, due to its suitable band gap and band-edge positions. However, predicting both of these properties is a challenging task for existing computational methods. Here, we show how Koopmans spectral functionals can accurately predict the band structure and level alignment of rutile, anatase, and brookite ${\mathrm{TiO}}_{2}$ using a computationally efficient workflow that only requires (a) a DFT calculation of the photocatalyst/vacuum interface and (b) a Koopmans spectral functional calculation of the bulk photocatalyst. The success of this approach for ${\mathrm{TiO}}_{2}$ suggests that this strategy could be deployed for assessing the suitability of novel photocatalyst candidates.
Fields of Study & Subjects
Machine Learning in Materials Science
Publication details
- Journal / source
- Physical Review Materials
- Publisher
- American Physical Society (APS)
- Volume
- 10
- Issue
- 2
- Publication date
- 12 February 2026
- Language
- EN